mindis / MSTL

Notebook to accompany MSTL article

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MSTL

This repo contains the notebook used to generate the figures in this article on MSTL.

Summary

In the notebook I show how to decompose a time series with multiple seasonal components using an algorithm called Multiple Seasonal-Trend decomposition using Loess (MSTL) in Python. I demo an implementation of MSTL that I contributed to Statsmodels and apply it to an electricity demand time series.

Installation

Create a virtual environment and pip install the requirements.

pip install -r requirements.txt

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Notebook to accompany MSTL article

License:BSD 3-Clause "New" or "Revised" License


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